THE EFFECTS OF PESTICIDES IN WATER RESOURCES

Environmental pollution is concerned problem all around world due to rapid increase of industrialization and urbanization. Especially, the intensive pesticide use has caused some environmental problems in many countries. The major problem occurred in water resources. Therefore, these resources need to be protected from the contamination of pesticides for future sustainable use

Machine learning for estimation of building energy consumption and performance:a review

Ever growing population and progressive municipal business demands for constructing new buildings are known as the foremost contributor to greenhouse gasses. Therefore, improvement of energy eciency of the building sector has become an essential target to reduce the amount of gas emission as well as fossil fuel consumption. One most eective approach to reducing CO2 emission and energy consumption with regards to new buildings is to consider energy eciency at a very early design stage. On the other hand, ecient energy management and smart refurbishments can enhance energy performance of the existing stock. All these solutions entail accurate energy prediction for optimal decision making. In recent years, articial intelligence (AI) in general and machine learning (ML) techniques in specic terms have been proposed for forecasting of building energy consumption and performance. This paperprovides a substantial review on the four main ML approaches including articial neural network, support vector machine, Gaussian-based regressions and clustering, which have commonly been applied in forecasting and improving building energy performance

COMMUNICATIONS FACULTY OF SCIENCES UNIVERSITY OF ANKARA-SERIES A1 MATHEMATICS AND STATISTICS

Rolling contact between two surfaces plays an important role in robotics and engineering such as spherical robots, single wheel robots, and multi-fingered robotic hands to drive a moving surface on a fixed surface. The rolling contact pairs have one, two, or three degrees of freedom (DOFs) consisting of angular velocity components. Rolling contact motion can be divided into two categories: spin-rolling motion and pure-rolling motion. Spin-rolling motion has three (DOFs), and pure-rolling motion has two (DOFs). Further, it is well known that the contact kinematics can be divided into two categories: forward kinematics and inverse kinematics. In this paper, we investigate the inverse kinematics of spin-rolling motion without sliding of one timelike surface on another timelike surface in the direction of timelike unit tangent vectors of their timelike trajectory curves by determining the desired motion and the coordinates of the contact point on each surface. We get three nonlinear algebraic equations as inputs by using curvature theory in Lorentzian geometry. These equations can be reduced as a univariate polynomial of degree six by applying the Darboux frame method. This polynomial enables us to obtain rapid and accurate numerical root approximations and to analyze the rolling rate as an output. Moreover, we obtain another outputs: the rolling direction and the compensatory spin rate

Vehicle Stock Dataset

Turkish vehicle stock between 1994 and 201

Vehicle Stock Dataset

Turkish vehicle stock between 1994 and 201

Vehicle Stock Dataset

Turkish vehicle stock between 1994 and 201

Green Electricity Data

Environmental awareness has increased the demand for green electricity, which is the electricity generated entirely from renewable energy sources. Green electricity is currently documented and tracked using energy attribute certificates. Before setting regulations and establishing the energy certificate system infrastructure, it is critical to analyze the demand and market value of the certificates and green electricity. This study aims to determine the demand for green electricity and the certificates, calculate the financial return of the certificates to renewable energy investors, and analyze the market value of the certificates. In the study, separate surveys were conducted to corporate consumers, electricity producers, and electricity suppliers to analyze their tendencies toward green electricity and the certificates. The analyses of the 348 survey responses indicate that 96% of corporate companies would prefer to use green electricity over standard electricity, and 20% stated that they would pay higher prices for green electricity than standard electricity. The economic analyses conducted within the study indicate that the certified green electricity supply could correspond to 63% of the total renewable energy sources-based electricity generation in 2020 (73.7 TWh). This amount would provide €59 million yearly additional income to renewable energy investors.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Data for: Techno-economical Analysis of Energy Efficiency Measures and Renewable Energy Technologies for Single Detached Homes

Data_1.xlsx: This spreadsheet includes the monitored natural gas and electricity, climate, natural gas and electricity tariff data. Data_2.xlsx: This spreadsheet includes software estimates for space heating and scenarios results